this post was submitted on 08 Jul 2024
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Bayesian purist cope and seeth.
Most machine learning is closer to universal function approximation via autodifferentiation. Backpropagation just lets you create numerical models with insane parameter dimensionality.
Any practical universal function approximation will go against entropy.